VP, Lakehouse & AI Data Platform Engineer

Goldman Sachs; Dallas (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Goldman Sachs is recruiting a Data Engineer to design, build and operate data pipelines on a modern Lakehouse and AI data platform. You will work across ingestion, transformation, modelling, optimization and data quality to deliver scalable data products for analytics and AI workloads.

Ideal candidates have 7–12+ years in data engineering, strong Python/Java skills and deep SQL expertise. The role emphasizes production-grade pipelines, tooling, and collaboration with platform teams to support

Qualifications

• 7–12+ years of experience in data engineering or related field.
• Strong programming experience in Python or Java.
• Proficient SQL skills and data analysis.
• Ability to design and optimize batch and streaming data pipelines.
• Experience with distributed processing frameworks and data formats.

Responsibilities

• Design, build, test and support data pipelines on a modern Lakehouse and AI platform.
• Develop raw, refined and curated datasets for analytics and AI use cases.
• Ensure data quality, reconciliation and testing across pipelines.
• Collaborate with engineering teams and data consumers to deliver data products on time.

Skills

Python

Java

SQL

CI/CD

Data architecture

Problem solving

Education

Bachelor's or Master's in CS/Data/Engineering

Tools

Apache Spark

Kafka

Snowflake

Databricks

Hadoop ecosystem

JSON/Parquet

Job description

Goldman Sachs is recruiting a Data Engineer to design, build and operate data pipelines on a modern Lakehouse and AI data platform. You will work across ingestion, transformation, modelling, optimization and data quality to deliver scalable data products for analytics and AI workloads.

Ideal candidates have 7–12+ years in data engineering, strong Python/Java skills and deep SQL expertise. The role emphasizes production-grade pipelines, tooling, and collaboration with platform teams to support